Providing context to your visualizations such as targets, comparisons to benchmarks, or predictions is key to helping viewers better understand the performance of the data they look at and take the right action. In other words, context helps users understand how good or bad their current performance is.
One common metric for context, especially when there are no targets available, is the performance of our metric in a previous period. For example, how many views were had on a specific web-page last week before launching a new campaign, etc.
This is very popular when your visualization is showing data over time - in this case, the number of page views per week. However, it can also be used when your visualization is simply filtered by time (i.e., your time dimension is on the visualization slicer and not the axes).
Here is an example of a chart showing the sales by country and comparing it to the sales in the previous year for that country. Using this chart, it is easy to see that only Germany and Australia surpassed their sales comparing to the previous year. Setting this up in Dundas BI is quite simple using the period-over-period comparisons.
